Abstract
Regional optimization of food consumption is an appropriate way to reduce food waste, improve sustainability in food consumption pattern, and increase the nutrition security of consumers. This study provides a comprehensive technique for calculating the nutrient efficiency score (NES) of Iranian households based on food consumption patterns during 2010–2018 using data envelopment analysis. This study calculates nutrient efficiency of humans in time series and provincial (spatial) format. The data and information are from the nationwide 227,083 household food consumption survey conducted by the Statistical Center of Iran. Factors affecting nutrient efficiency were determined through the estimation of a panel data model. We found that Iranian households can increase their nutrient efficiency by decreasing 20% of their current consumption of food items in rural areas. The provinces of Sistan-Baluchistan and Khuzestan had the least NES in both rural and urban areas. The age of the household breadwinner, educational level, and female-headed households were significantly and positively associated with the NES. Based on these findings, the government can increase the NES by investing in education and job creation to help improve incomes without of the allocation of untargeted subsidies which are currently distributed among Iranian households.
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The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
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Abbreviations
- BCC:
-
Banker, charnes, and cooper
- Cal:
-
Calorie
- CCR:
-
Charnes, cooper, & rhodes
- CRS:
-
Constant return to scale
- CPS:
-
Convex program subset
- DEA:
-
Data envelopment analysis
- DMUs:
-
Decision-making units
- EMS:
-
Efficiency measurement system
- FAO:
-
Food and agriculture organization
- FCO:
-
Food consumption optimization
- GAMS:
-
General algebraic modeling system
- gr:
-
Gram
- NES:
-
Nutrient efficiency score
- m2:
-
Square meter
- SCI:
-
Statistical center of Iran
- TV:
-
Television
- VRS:
-
Variable return to scale
- STATA:
-
Software for statistics and data science
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Acknowledgements
We gratefully acknowledge all supports provided by the Department of Agricultural Economics and Rural Development, Faculty of Agriculture, Lorestan University, Khorramabad, Iran. We would like to express our gratitude to Prof. Haider A. Khan and Dr. Abbas Hashemi for their help in the primary steps of the present study.
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Pakravan-Charvadeh, M.R., Flora, C. Sustainable food consumption pattern with emphasis on socioeconomic factors to reduce food waste. Int. J. Environ. Sci. Technol. 19, 9929–9944 (2022). https://doi.org/10.1007/s13762-022-04186-9
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DOI: https://doi.org/10.1007/s13762-022-04186-9